Humans are able to infer causal relationships from samples that are too small for statistical tests to produce significant results [1]}. This ability is seemingly at odds with assumptions that are at the center of many popular algorithms for learning causal graphical models, which often require statistical testing of independence claims using large samples of observations [2]}, [3]}, [4]}.
